实时流处理工具，用于检测可疑的网络模式使用机器学习

Proceedings of the 15th International Conference on Availability, Reliability and Security Pub Date : 2020-08-25 DOI:10.1145/3407023.3409189

Mikołaj Komisarek, M. Choraś, R. Kozik, M. Pawlicki

{"title":"实时流处理工具，用于检测可疑的网络模式使用机器学习","authors":"Mikołaj Komisarek, M. Choraś, R. Kozik, M. Pawlicki","doi":"10.1145/3407023.3409189","DOIUrl":null,"url":null,"abstract":"In this paper, the performance of stream processing and accuracy in the prediction of suspicious flows in simulated network traffic is investigated. In addition, concepts of an engine that integrates with novel solutions like the Elastic-search database and Apache Kafka that allows easy definition of streams and implementation of any machine learning algorithm are presented.","PeriodicalId":121225,"journal":{"name":"Proceedings of the 15th International Conference on Availability, Reliability and Security","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Real-time stream processing tool for detecting suspicious network patterns using machine learning\",\"authors\":\"Mikołaj Komisarek, M. Choraś, R. Kozik, M. Pawlicki\",\"doi\":\"10.1145/3407023.3409189\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, the performance of stream processing and accuracy in the prediction of suspicious flows in simulated network traffic is investigated. In addition, concepts of an engine that integrates with novel solutions like the Elastic-search database and Apache Kafka that allows easy definition of streams and implementation of any machine learning algorithm are presented.\",\"PeriodicalId\":121225,\"journal\":{\"name\":\"Proceedings of the 15th International Conference on Availability, Reliability and Security\",\"volume\":\"16 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-08-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 15th International Conference on Availability, Reliability and Security\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3407023.3409189\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 15th International Conference on Availability, Reliability and Security","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3407023.3409189","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 8

摘要

本文研究了模拟网络流量中流处理的性能和可疑流预测的准确性。此外，还介绍了一个引擎的概念，该引擎集成了Elastic-search数据库和Apache Kafka等新颖的解决方案，可以轻松定义流和实现任何机器学习算法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Real-time stream processing tool for detecting suspicious network patterns using machine learning

In this paper, the performance of stream processing and accuracy in the prediction of suspicious flows in simulated network traffic is investigated. In addition, concepts of an engine that integrates with novel solutions like the Elastic-search database and Apache Kafka that allows easy definition of streams and implementation of any machine learning algorithm are presented.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Proceedings of the 15th International Conference on Availability, Reliability and Security

自引率

0.00%

发文量